Quantum Information Processing最新文献

Two-way quantum key distribution (TWQKD) holds great potential for achieving high secure key rates over a certain transmission distance range. However, in practice, flaws in measurement detectors (the primary source of security loopholes) in TWQKD are vulnerable to side-channel attacks, potentially leading to undetectable key leakage. To tackle this problem and enhance the key performance of TWQKD, this paper introduces a measurement-device-independent high-dimensional TWQKD protocol (MDI-HD-TWQKD). The security formula for this protocol is derived, and its key performances are simulated under an imperfect devices model based on current technology. The results indicate that TWQKD can deliver high performance when utilizing high-dimensional sources in the measurement-device-independent scenario.

In this paper, we have investigated the features of tripartite quantum-memory-assisted entropic uncertainty (tQMA-EU) and its two corresponding lower bounds in three-qubit Heisenberg XXZ spin chain model with Dzyaloshinskii–Moriya (DM) interaction and Kaplan–Shekhtman–Entin–Wohlman–Aharony (KSEA) interaction. The results show that, when the DM and KSEA interaction are taken account, the Dolatkhah’s lower bound is always equal to the tQMA-EU and remains higher than the Ming’s lower bound in both ferromagnetic and antiferromagnetic cases. The increasing of DM and KSEA interactions can effectively reduce the value of tQMA-EU, the varying behaviors of tQMA-EU with respect to DM and KSEA interactions from positive and negative intervals demonstrate central symmetry. Particularly, in ferromagnetic case, this reduction effect is more pronounced than that in antiferromagnetic case. In addition, the dynamical features of Dolatkhah’s lower bound and Ming’s lower bound with respect to the spin chain systemic parameters display distinct differences in the ferromagnetic and antiferromagnetic cases. Specifically, in the ferromagnetic case and with weak DM interaction, during the lower temperature range, under the influence of the KSEA interaction and under an external magnetic field, the Dolatkhah’s lower bound dosen’t negatively correlated to tripartite negativity quantum correlation (mathcal {N}_{ABC}). in contrast, the dynamics of Ming’s lower bound show negative-correlated to (mathcal {N}_{ABC}).

We address the issue of multi-shot discrimination between two qubit channels by invoking a simple adaptive protocol that employs Helstrom measurement at each step and classical information feedforward, beside separable inputs. We contrast the performance of Bayesian and Markovian strategies. We show that the former is only slightly advantageous and for a limited parameters’ region.

One of the key operations in various quantum algorithms, including Grover’s algorithm, is the multi-controlled Toffoli (MCT) gate. This work proposes optimal design techniques for the MCT gate using the conditionally clean ancillae strategy, assuming that an arbitrary number of clean ancillae are available. We consider two primary cases: first, when only a single clean ancilla is available; and second, when the number of clean ancillae is (mathcal {O}(n)), where n is the number of controls in the MCT gate. For the case of a single clean ancilla, we propose a novel design method that achieves better efficiency compared to a previous approach. While prior work yields a Toffoli-depth of (mathcal {O}(n)), our proposed method reduces the Toffoli-depth to (mathcal {O}(sqrt{n})). Moreover, by employing this new technique as a subroutine within previously proposed methods for the cases of two or three clean ancillae, we demonstrate both logically and empirically an improvement in time complexity. Additionally, prior work addressed optimal designs only when the number of clean ancillae was up to approximately (log n), without providing efficient strategies beyond this regime. In this study, we also present efficient MCT gate constructions when a sufficiently large number of clean ancillae are available. We confirm, both theoretically and empirically, that the Toffoli-depth decreases as the number of clean ancillae increases. In conclusion, this work highlights that the optimal MCT design strategy depends on the availability of clean ancillae. It also indirectly suggests a threshold point at which the optimal design strategy transitions, depending on the number of ancillae provided.

In this work, we consider a novel heuristic decomposition algorithm for n-qubit gates that implement specified amplitude permutations on sparse states with m non-zero amplitudes. These gates can be useful as an algorithmic primitive for higher-order algorithms. We demonstrate this by showing how it can be used as a building block for a novel sparse state preparation algorithm, Cluster Swaps, which is able to significantly reduce CX gate count compared to alternative methods of state preparation considered in this paper when the target states are clustered, i.e., such that there are many pairs of non-zero amplitude basis states whose Hamming distance is 1. Cluster Swaps can be useful for amplitude encoding of sparse data vectors in quantum machine learning applications.

This paper constructs a quantum commons game model based on the homogeneous rational expectation theory and the Li–Du–Massar (LDM) quantization scheme and conducts a comparative analysis of its differences from the classical commons problem. Studies have found that within a specific range, the enhancement of quantum entanglement can expand the stable region of the system, increase the threshold of system bifurcation, and play a regulatory role in the complex dynamic behaviors of the model. When the farmers’ adjustment speed exceeds the critical threshold, the system will exhibit chaotic behavior accompanied by a bifurcation phenomenon. By introducing the delayed feedback control method, the chaotic behavior of the complex dynamic system can be redirected and stabilized at the quantum Nash equilibrium point. In addition, through numerical simulations, the correctness and effectiveness of the theoretical model are verified from the perspectives of the bifurcation diagram, the maximum Lyapunov exponent, and the strange attractor.

Quantum secret sharing (QSS) is essential for secure multi-party information distribution. However, existing multi-party quantum secret sharing (MQSS) protocols suffer from several limitations, such as requiring the distributor to know each participant’s secret in advance, low efficiency, challenging quantum resource preparation, and complex operations. This paper proposes an efficient MQSS protocol based on single photons. The protocol utilizes single photons and simple local unitary operations for secret distribution. Participants are not required to perform measurements, which reduces the difficulty of resource preparation and improves operability. By incorporating decoy particles, the protocol can ideally achieve 100% efficiency. Security analysis demonstrates its robustness against common attacks. Compared with existing protocols, the proposed scheme excels in terms of quantum resource requirements, the distributor’s prior knowledge of secrets, and qubit efficiency. Simulations on the IBM quantum platform confirm its feasibility.

The classical games of Rock-Paper-Scissors (RPS) and its extended variant, Rock-Paper-Scissors-Lizard-Spock (RPSLS), exemplify non-transitive logic and mixed-strategy Nash equilibria in game theory. This work presents a novel quantum implementation of these games using Grover’s search algorithm, demonstrating how quantum superposition and entanglement can transform classical gameplay. We develop a quantum circuit architecture that efficiently identifies winning strategies, with the RPSLS variant highlighting the scalability of our approach to larger strategy spaces. Furthermore, we introduce a novel quantum bit commitment protocol based on non-orthogonal RPSLS states, which serves as a pedagogical model for understanding security trade-offs in quantum cryptography. Our framework reveals deep parallels between the cyclic dominance of game strategies and quantum nonlocality through Hardy’s paradox, while offering practical applications in quantum optimization and secure communication. The proposed implementation is experimentally feasible on near-term quantum devices and provides an accessible platform for illustrating quantum algorithmic advantages in strategic decision-making.

With the rapid advancement of quantum computing, the security of classical blockchain systems is facing severe challenges. The emergence of quantum blockchain offers a promising solution to fundamentally address these issues. Consortium blockchains, due to their inherent characteristics, are particularly well-suited for the deployment and implementation of quantum blockchains at the current stage. This paper proposes a novel quantum consensus mechanism named Q-PnV (Quantum Proof and Voting), tailored for consortium blockchains. The consensus extends the classical Proof of Vote (PoV) consensus mechanism into the quantum domain and innovatively integrates quantum voting, quantum identity authentication, and quantum random number generation technologies. By combining Q-PnV with a quantum blockchain architecture based on weighted hypergraph states, this work presents a comprehensive quantum blockchain solution for consortium scenarios. Theoretical analysis demonstrates that, compared to classical approaches, a quantum blockchain based on Q-PnV not only effectively resists quantum attacks, but also significantly enhances the security and fairness of the consensus process, thereby providing a reliable foundation for consortium blockchain applications in a future quantum computing environment.

Finding controls for open quantum systems needs to take into account effects from unwanted environmental noise. Since actual realisations or states of the noise are typically unknown, the usual treatment for the quantum system’s decoherence dynamics is via the so-called Lindblad master equation, which in essence describes an average evolution (mean path) of the system’s state affected by the unknown noise. We here consider an alternative view of a noise-affected open quantum system, where the average dynamics can be unravelled into hypothetical noisy quantum trajectories, and propose a control strategy for the state preparation problem based on the likelihood of noise occurrence. We formulate a stochastic path integral for noise variables whose extremum yields control functions associated with a most-likely noise to achieve target states. As a proof of concept, we apply our method to a qubit state preparation under dephasing noise and analytically solve for controlled Rabi drives for arbitrary target states. Since the method is constructed based on the probability of noise, we also introduce a fidelity success rate as a measure of the state preparation. We benchmark against the mean-path approaches, e.g., GRAPE and CRAB controls, using both average fidelity and a success rate metric. While standard mean-path controls maximise average fidelity, most-likely controls achieve higher success rates, especially at strong dephasing.